class_docstr: Abstract clusterer which takes tokens and maps them into a vector space.
  Optionally performs singular value decomposition to reduce the
  dimensionality.
docstr: Returns the vector after normalisation and dimensionality reduction
docstr_tok: ["Returns","the","vector","after","normalisation","and","dimensionality","reduction"]
code: def vector(self, vector):
      """
      Returns the vector after normalisation and dimensionality reduction
      """
      if self._should_normalise:
          vector = self._normalise(vector)
      if self._Tt is not None:
          vector = numpy.dot(self._Tt, vector)
      return vector
  
imports: import copy
  from abc import abstractmethod
  from math import sqrt
  from sys import stdout
  from nltk.cluster.api import ClusterI
label_desc: Use image node_id 8 for calling the VectorSpaceClusterer obj's underlying member method code with example usage: obj.vector(vector) and returns: vector